embeddings

app.py

@@ -1,6 +1,5 @@
 from langchain.docstore.document import Document
 """Core Modules s"""
-from typing import Union, Optional, List, Sequence
 from langchain.embeddings.openai import OpenAIEmbeddings
 from langchain.text_splitter import RecursiveCharacterTextSplitter, NLTKTextSplitter, CharacterTextSplitter
 from langchain.vectorstores.faiss import FAISS
@@ -45,7 +44,7 @@ def doc_to_embeddings(doc:Document, split_mode:str='tiktoken',
     else:
         raise ValueError("Please specify the split mode.")
     documents = text_splitter.split_documents(doc)
-    embeddings = OpenAIEmbeddings()
+    embeddings = OpenAIEmbeddings(openai_api_key=os.environ['OpenAI_APIKEY'])
     faiss_db = FAISS.from_documents(documents, embeddings)
     if save_faiss:
         faiss_db.save_local(faiss_save_path)